Research On New Key Technologies Of Intelligent Information Transmission For Internet Of Vehicles

As a new form of industry,which is deeply integrated with automobile driving,electronic information,traffic transportation and so on,the Io V(Internet of Vehicles)has increasingly become an important direction for each country to develop.Based on the inter-vehicle network,intra-vehicle network,and vehicle Ad-hoc network,the Io V,making use of the advanced technologies of artificial intelligence,information processing,communication,electronic sensing and control,conducts wireless communication and information exchange between the vehicles and X(X: vehicles,road,pedestrians,the service platform),which is an integrated network to realize intelligent transportation,information service and vehicle intelligent control.The Io V is a typical high-speed mobile communication network,which involves the information transmission,interaction,reorganization,background data analysis,decision support and other processes in the dynamic traffic scene.The efficient,reliable and intelligent transmission of information among various communication scenes is the core and key of the research.Due to the special application environment and high mobility of vehicles,the Io V has many problems in wireless communication,such as frequent changes in banded topology,unreliability of routing connection,longer delay in link transmission,missing and low quality in collecting data,etc.The dissertation focuses on the above key issues of intelligent information transmission in the Io V,and has studied the following three key technologies: message broadcast distribution,data missing estimation and data packet routing transmission.That is to say,the topic of this dissertation is the “Research on New Key Technologies of Intelligent Information Transmission for Io V”,the specific research contents and innovations of this paper are as follows:(1)In term of message distribution in the Io V,we propose a new method of intelligent distribution based on cross-layer messages(CLCBF,Cross-Layer Contention-Based Forwarding),which can restrain the occurrence of local-broadcast storms,and improve the timeliness and high-effectiveness of information transmission.Specifically,the method analyzes and studies the redundant spurious distribution,then establishes mathematical model to calculate and evaluate key performance indicators.Furthermore,the adaptive transmission control based on cross-layer delay-based forwarding is implemented.The method is verified by Monte-Carlo simulation of vehicle node flow.The results of experiments demonstrate the proposed method can improve the performance of distributed message distribution,and effectively promote the intelligence level of data transmission in the Io V.(2)In terms of data missing estimation for the Io V,we propose a new method of data missing estimation with tensor heterogeneous ensemble learning based on FNN(FTEL,FNN-Based Tensor Ensemble Learning),which can deal with the lack of data,abnormal data,and other low-quality problems.Firstly,this method builds a tensor model based on the characteristics of traffic flow data in the Io V.Then,the heterogeneous ensemble method is introduced into traffic data imputation modeling.Furthermore,by using Fuzzy Neural Network optimization to perform tensor decomposition adaptive dynamic weighted ensemble,and effectively improves the accuracy of imputation.The applicability and effectiveness of the algorithm are proved by the empirical study.The accurate imputation results can be obtained under the circumstances of random data elements missing and spectral structural data.(3)In term of the data packet routing transmission of the Io V,we propose a new method of reliable data transmission based on group intelligence perception strategy(VGCD,Vehiclar Grouping-Communicated Data),which can improve the reliability and effectiveness of information transmission.Based on the new application of urban environment monitoring in the Io V,the method is an integrated design,which is divided into two parts: one is the perception monitoring and collection,based on the city air quality collection of vehicle group intelligence perception collaborative monitoring,to avoid information redundancy and communication overload,the other part is the data transmission in which a reliable data transmission minimum delay hybrid routing method is proposed.The algorithm combines the coding mechanism with the routing design,merges the routing switching ideas,and makes probability-based routing decisions with the goal of minimizied delay.In the linear road section,the fuzzy logic prediction based vehicle adaptive connectivity clustering routing algorithm is adopted to reduce the communication overhead in the process of vehicle collaboration and ensure the high connectivity of the network.At intersections,routing decision based on probability is adopted to reduce information transmission delay.The results of experiments demonstrate the proposed method can effectively improve the efficiency of data acquisition and transmission,and increase reliability.